Key message A novel multi-environment competition individual-tree mixed model resulted in better fit, and greater individual narrow- and broad-sense heritabilities than the model without competition, notably for traits showing competition. In multi-environment tests, the proposed model would allow tree breeders to select genotypes with the best performance in both additive direct and competition breeding values, increasing forest productivity. Context Genetic merit of trees is known to be affected and interact with local competition effects as well as changes across environmental conditions. Recent studies showed that competition genetic effects can affect the genetic variance and bias the tree breeding values, and its covariance with direct breeding values has been variable across traits. Aims The present paper extends a mixed-model methodology to the problem of accounting for competition in a multi-environment set of forest genetic trials and exploring its impact on genetic variances as well as the multi-environment genetic correlation. Methods The proposed model is illustrated using data from two full-sib trials of Pinus elliottii var. elliottii × Pinus caribaea var. hondurensis F 1 . Dispersion parameters and (co)variance of total breeding values were estimated for diameter at breast height, total tree height, and stem straightness at age 10. Results For traits showing competition effects (diameter at breast height and total tree height), the proposed multi-environment competition model gave better fit than the simpler model. Accounting for competition increased the direct additive variance, reduced the residual variances, and did not change significantly the across-site additive genetic correlation. However, for diameter at breast height, top 5% best genetic rankings showed differences. Conclusion When traits are strongly affected by inter-tree competition, the use of the proposed model in multi-environment analyses can efficiently identify the phenomenon with general benefits in the fitting of genetic components and open the door to select on the basis of competitiveness.

中文翻译：

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考虑多环境树木遗传评估中的竞争：以杂交松树为例

关键信息 一种新颖的多环境竞争个体-树混合模型比没有竞争的模型具有更好的拟合度和更大的个体狭义和广义遗传力，尤其是表现出竞争的性状。在多环境测试中，所提出的模型将允许树木育种者选择在加性直接和竞争育种值方面具有最佳性能的基因型，从而提高森林生产力。背景 已知树木的遗传价值会受到影响并与当地竞争效应以及环境条件的变化相互作用。最近的研究表明，竞争遗传效应会影响遗传方差并使树木育种值产生偏差，并且其与直接育种值的协方差在性状之间是可变的。目的 本文将混合模型方法扩展到在多环境森林遗传试验集中解释竞争的问题，并探索其对遗传变异和多环境遗传相关性的影响。方法 所提出的模型使用来自松树变种的两个全同胞试验的数据进行说明。elliottii × 加勒比松变种。洪都拉斯 F 1 . 根据胸高直径、总树高和 10 岁时的茎直度估计了总育种值的分散参数和（协）方差。 结果对于显示竞争效应的性状（胸高直径和总树高），建议的多-环境竞争模型比更简单的模型更适合。考虑竞争增加了直接加性方差，减少了剩余方差，并且没有显着改变跨位点加性遗传相关性。然而，对于胸高直径，前 5% 的最佳遗传排名显示出差异。结论当性状受到树间竞争的强烈影响时，在多环境分析中使用所提出的模型可以有效地识别遗传成分拟合中具有普遍益处的现象，并为基于竞争力的选择打开大门。